SPUR: Enhancing Cyclist Safety through Digital City Twins – A Data-Driven Infrastructure Planning and VR Simulation Approach

Cyclist safety in urban areas is a growing concern that requires innovative planning and citizen participation approaches. This research introduces SPUR, a serious gaming application designed to evaluate cyclist safety on a city scale through a data-driven traffic infrastructure analysis and immersive evaluation of the current state of the traffic network and planned alternatives. The concept of SPUR introduces a digital city twin that uses data from city models, road infrastructure, point clouds, geo-referenced statistics, and citizen feedback to identify vulnerabilities and guide towards safer planning alternatives. Users are given assistance for interactively generating planning scenarios in an editor and can create simulations that are made tangible with a VR setup with a functional bicycle and a traffic simulation based on SUMO, ensuring realistic scenarios for the evaluation. While this approach focuses on cyclist safety, the workflow is generally applicable to other use cases in urban and traffic infrastructure planning.

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Publication Details

Published
2025-06-23
DOI
https://doi.org/10.1109/ie64880.2025.11130085
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
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article

SPUR: Enhancing Cyclist Safety through Digital City Twins – A Data-Driven Infrastructure Planning and VR Simulation Approach

Uwe Rüppel, Michael Disser
Traffic Prediction and Management Techniques
article

SPUR: Enhancing Cyclist Safety through Digital City Twins – A Data-Driven Infrastructure Planning and VR Simulation Approach

Uwe Rüppel, Michael Disser
article en

Abstract

Cyclist safety in urban areas is a growing concern that requires innovative planning and citizen participation approaches. This research introduces SPUR, a serious gaming application designed to evaluate cyclist safety on a city scale through a data-driven traffic infrastructure analysis and immersive evaluation of the current state of the traffic network and planned alternatives. The concept of SPUR introduces a digital city twin that uses data from city models, road infrastructure, point clouds, geo-referenced statistics, and citizen feedback to identify vulnerabilities and guide towards safer planning alternatives. Users are given assistance for interactively generating planning scenarios in an editor and can create simulations that are made tangible with a VR setup with a functional bicycle and a traffic simulation based on SUMO, ensuring realistic scenarios for the evaluation. While this approach focuses on cyclist safety, the workflow is generally applicable to other use cases in urban and traffic infrastructure planning.

Numerical Method (China) (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 76%
Traffic Prediction and Management Techniques
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